一类截尾数据下失效模式不确定元作用单元寿命分布的参数估计

IF 1.7 4区 工程技术 Q3 ENGINEERING, INDUSTRIAL
Xiao Zhu, Y. Ran, Xinglong Li, Liming Xiao
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引用次数: 0

摘要

本文提出了一类截尾数据下具有不确定失效模式的元动作单元(MAU)寿命分布的参数估计方法。将MAU视为完成机械设备功能的基本功能单元,并根据Meta-Action (MA)中的异常运动参数对其失效模式进行分类,比传统的零件机械失效模式更简洁。然而,由于技术限制和空间可及性的限制,MAU的失效数据和截割数据中存在一些不确定信息,这些不确定信息会影响MAU寿命分布的参数估计。为了避免对分布参数估计精度的影响,针对失效数据和截尾数据的可信程度,构造了基于信念函数理论的证据似然函数。此外,提出了证据期望最大化(E2M)算法来估计i型截尾数据下MAU寿命混合指数分布的参数。最后,以自动换板机(APC)为例,验证了MAU失效模式分类的有效性。通过对E2M算法的仿真表明,所提参数估计方法能够综合故障数据和截除数据中的不确定性信息,得到比传统的期望最大化方法更稳定的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Parameter estimation of lifetime distribution for the meta-action unit with uncertainty failure modes under type-I censored data
This paper presents a parameter estimation method for the lifetime distribution of the Meta-Action Unit (MAU) with uncertainty failure modes under type-I censored data. The MAU is regarded as the basic functional unit to accomplish the function of mechanical equipment, and its failure modes are classified according to the abnormal kinematic parameters in Meta-Action (MA), which are more succinct than the traditional mechanical failure modes on parts. However, there is some uncertain information about the failure data and censored data of MAU because of the technology limitations and the space accessibility constraints for monitoring the kinematic parameters of MA, which uncertainty information can impact the parameter estimates of MAU lifetime distribution. In order to avoid the impacts on the estimating accuracy of distribution parameters, the evidential likelihood function based on the belief function theory is constructed in view of the credibility level of the failure data and censored data. In addition, the Evidential Expectation Maximization (E2M) algorithm is proposed to estimate the parameters of the mixed exponential distribution of MAU lifetime under type-I censored data. Finally, an application of an Automatic Pallet Changer (APC) is used to illustrate the validity of the MAU failure modes classification. The simulations of the E2M algorithm are conducted to show that the proposed parameters estimation method can integrate uncertain information in the failure data and the censored data, and obtain more stable results than those based on the conventional Expectation-Maximization (EM).
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来源期刊
CiteScore
4.50
自引率
19.00%
发文量
81
审稿时长
6-12 weeks
期刊介绍: The Journal of Risk and Reliability is for researchers and practitioners who are involved in the field of risk analysis and reliability engineering. The remit of the Journal covers concepts, theories, principles, approaches, methods and models for the proper understanding, assessment, characterisation and management of the risk and reliability of engineering systems. The journal welcomes papers which are based on mathematical and probabilistic analysis, simulation and/or optimisation, as well as works highlighting conceptual and managerial issues. Papers that provide perspectives on current practices and methods, and how to improve these, are also welcome
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